penguins_summary %>%
  gt() %>%
  tab_header(title = "Palmer Penguin Measurements")

penguins_summary %>%
  gt() %>%
  tab_header(title = "Palmer Penguin Measurements") %>%
  cols_label(
    species = "Species",
    mean_bill_length = "Bill Length (mean)",
    mean_bill_depth = "Bill Depth (mean)",
    mean_flipper_length = "Flipper Length (mean)"
  )

penguins_summary %>%
  gt() %>%
  tab_header(title = "Palmer Penguin Measurements") %>%
  fmt_number(
    columns = c(mean_bill_length, mean_bill_depth, mean_flipper_length),
    decimals = 2
  ) %>%
  cols_label(
    species = "Species",
    mean_bill_length = "Bill Length (mean)",
    mean_bill_depth = "Bill Depth (mean)",
    mean_flipper_length = "Flipper Length (mean)"
  )

penguins_summary %>%
  gt() %>%
  tab_header(title = "Palmer Penguin Measurements") %>%
  tab_spanner(
    label = "Mean Measurements (mm)",
    columns = c(mean_bill_length, mean_bill_depth, mean_flipper_length)
  ) %>%
  cols_label(
    species = "Species",
    mean_bill_length = "Bill Length",
    mean_bill_depth = "Bill Depth",
    mean_flipper_length = "Flipper Length"
  )

penguins_summary %>%
  gt() %>%
  tab_header(title = "Palmer Penguin Measurements") %>%
  tab_spanner(
    label = "Mean Measurements (mm)",
    columns = c(mean_bill_length, mean_bill_depth, mean_flipper_length)
  ) %>%
  cols_label(
    species = "Species",
    mean_bill_length = "Bill Length",
    mean_bill_depth = "Bill Depth",
    mean_flipper_length = "Flipper Length"
  ) %>%
  cols_align(
    align = "center",
    columns = everything()
  )

penguins_summary %>%
  gt() %>%
  data_color(
    columns = c(mean_bill_length, mean_flipper_length),
    fn = scales::col_numeric(palette = "Blues", domain = NULL)
  )

penguins_summary %>%
  gt() %>%
  tab_options(
    table.font.size = px(14),
    table.font.names = "Arial"
  )

penguins_summary %>%
  gt() %>%
  tab_style(
    style = cell_fill(color = "lightgray"),
    locations = cells_body(
      rows = mean_flipper_length > 200
    )
  )

penguins_summary %>%
  gt() %>%
  tab_style(
    style = cell_borders(
      sides = c("top", "bottom"),
      color = "black",
      weight = px(2)
    ),
    locations = cells_column_labels()
  )

penguins_summary %>%
  gt() %>%
  tab_style(
    style = cell_borders(
      sides = c("top", "bottom"),
      color = "black",
      weight = px(2)),
    locations = cells_column_labels())%>%
  tab_style(
    style = cell_borders(
      sides = c("bottom"),
      color = "black",
      weight = px(2)),
    locations = cells_body(rows = nrow(penguins_summary)))%>%
    tab_options(
    table.border.top.style = "none",
    table.border.bottom.style = "none",
    table_body.hlines.style = "none")

penguins_summary %>%
  gt(rowname_col = "species") %>%
  tab_stubhead(label = "Penguin Species")

penguins_summary %>%
  gt() %>%
  fmt_number(
    columns = c(mean_bill_length, mean_bill_depth, mean_flipper_length),
    decimals = 2,
    pattern = "{x} mm"
  )

penguins_summary %>%
  gt() %>%
  tab_spanner(
    label = "Bill Measurements (mm)",
    columns = c(mean_bill_length, mean_bill_depth)
  ) %>%
    tab_spanner(
    label = "Flipper Measurements (mm)",
    columns = c(mean_flipper_length)
  ) %>%
    cols_label(
    species = "Species",
    mean_bill_length = "Length",
    mean_bill_depth = "Depth",
    mean_flipper_length = "Length"
  )

penguins_summary %>%
  gt() %>%
  tab_footnote(
    footnote = "Data represents mean values per species.",
    locations = cells_column_labels(
      columns = c(mean_bill_length, mean_flipper_length)
    )
  )

penguin_trends %>%
  gt(rowname_col = "species") %>%
  cols_label(
    Year_2007 = "2007", # Adjust based on actual years in the dataset
    Year_2008 = "2008", # Adjust based on actual years in the dataset
    Year_2009 = "2009", # Adjust based on actual years in the dataset
    trend = "Density"
  ) %>%
  gt_plt_dist(
    column = trend, # Specify the column with the list of values
    type = "density" # Use density plots
  ) %>%
  tab_header(
    title = "Penguin Bill Length Trends",
    subtitle = "Mean bill lengths by year and density plot of all values"
  )

library(kableExtra)
penguin_summary %>%
  kable() %>%
  kable_styling()

penguins_summary %>%
  group_by(species) %>%
  kable() %>%
  kable_styling() %>%
  add_header_above(c("Species Data" = 4))

penguins_summary %>%
  kable(caption = "Penguin Bill Measurements") %>%
  kable_styling()

penguins_summary %>%
  kable(row.names = TRUE) %>%
  kable_styling()

penguins_summary %>%
  kable() %>%
  add_header_above(c(" " = 1, "Bills" = 2, "Flippers"))

penguins_summary %>%
  kable() %>%
  kable_styling(full_width = FALSE) %>%
  column_spec(1, border_right = TRUE)

penguins_summary %>%
  kable() %>%
  row_spec(1, bold = TRUE) %>%
  row_spec(3, italic = TRUE)

penguins_summary %>%
  kable() %>%
  kable_styling(font_size = 20) %>%
  add_footnote("Measurements are in millimeters.", , notation = "alphabet"
  )

penguins_summary %>%
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed"))

penguins_summary %>%
  kable() %>%
  kable_styling() %>%
  add_header_above(c(" " = 1, "Measurements" = 3)) %>%
  row_spec(0, bold = TRUE, color = "white", background = "black")

penguins_summary %>%
  kable() %>%
  row_spec(2, bold = TRUE, color = "red")

penguins_summary %>%
  kable() %>%
  column_spec(2, color = "red")

penguins_summary %>%
  kable() %>%
  kable_styling(font_size = 20)

library(reactable)
library(reactablefmtr)

reactable(penguins_summary)

reactable(
  penguins_summary,
  columns = list(
    mean_bill_length = colDef(name = "Mean Bill Length (mm)"),
    mean_bill_depth = colDef(name = "Mean Bill Depth (mm)"),
    mean_flipper_length = colDef(name = "Mean flipper Length (mm)")))

color_set <- c("#f7c844","#429460","#2e6d9e")

reactable(
  penguins_summary,
  columns = list(
    mean_bill_length = colDef(
      cell = color_tiles(penguins_summary, 
                         color_set))))

reactable(
  penguins_summary,
  rowStyle = function(index) {
    if (penguins_summary$mean_bill_length[index] > 45) {
      list(background = "lightblue")
    } else {
      NULL
    }
  }
)

reactable(
  penguins_summary,
  rownames = TRUE
)

reactable(
  penguins_summary,
  bordered = TRUE
)

reactable(
  penguins,
  pagination = TRUE,
  defaultPageSize = 3
)

reactable(
  penguins_summary,
  columns = list(
    mean_flipper_length = colDef(
      maxWidth = 280,
      align = "center",
      cell = data_bars(
        data = penguins_summary,
        fill_color = c("#f7c844", "#429460", "#2e6d9e"),
        number_fmt = scales::number_format(accuracy = 0.2)
      ),
      style = list(borderLeft = "1px dashed rgba(0, 0, 0, 0.3)")
    )
  )
)

reactable(
  penguins_summary,
  pagination = TRUE,
  defaultPageSize = 3,
  searchable = TRUE,
)

library(flextable)

penguins_summary %>%
  flextable()

penguins_summary %>%
  flextable() %>%
  set_caption("Penguins Summary Table")

penguins_summary %>%
  flextable() %>%
  add_footer_lines("This table summarizes penguin measurements.")

penguins_summary %>%
  flextable() %>%
    set_header_labels(
    mean_bill_length = "Mean Bill Length (mm)",
    mean_bill_depth = "Mean Bill Depth (mm)",
    mean_flipper_length = "Mean Flipper Length (mm)"
  )

penguins_summary %>%
  flextable() %>%
    highlight(i = 1, color = "yellow")

penguins_summary %>%
  flextable() %>%
    color(i = ~ mean_bill_length < 48, color = "red")

penguins_summary$row_num <- seq_len(nrow(penguins_summary))

flextable(penguins_summary) %>%
  colformat_int(j = "row_num")

penguins %>%
  slice(1:10) %>%
  flextable() %>%
  merge_v(j = c("island","year"))

penguins_summary %>%
  flextable() %>%
   align(j = "mean_bill_length", align = "center")

penguins_summary %>%
  flextable() %>%
   bg(j = "species", bg = "lightblue")

penguins_summary %>%
  flextable() %>%
  color(j = "mean_bill_depth", color = "orange")

penguins_summary %>%
  flextable() %>%
  fontsize(part = "body", size = 20)

penguins_summary %>%
  flextable() %>%
  bold(j = "species", bold = TRUE)

penguins_summary %>%
  flextable() %>%
    rotate(j = "species", rotation = "btlr")

penguins_summary %>%
  flextable() %>%
  theme_vanilla()

penguins_summary %>%
  flextable() %>%
  theme_alafoli()

penguins_summary %>%
  flextable() %>%
    bg(i = seq(1, nrow(penguins_summary), by = 2), bg = "gray90")